Results 261 to 270 of about 1,306,676 (292)
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Multivariate Analysis in Twins
Acta geneticae medicae et gemellologiae, 1970We present the results of a noncentral χ2 test applied to 63 like-sexed twin pairs.We have separated the pairs into two groups: 30 serologically identical and 33 serologically nonidentical pairs for nine sera of the blood groups ABO, MN, and Rh.The probabilities of monozygosity of the serologically identical pairs, calculated by the method of Maynard ...
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Multivariate Analysis of Variance
Journal of Marketing Research, 1987Introduction to Multivariate Analysis of Variance Omnibus MANOVA Tests Analyzing and Interpreting Significant MANOVAs Causal Models Underlying MANOVA Analyses Complex Designs Overview of Computer Programs for ...
D. D. V. Morgan +2 more
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2004
In this paper we will analyze data obtained from a fuzzy set, where samples are defined using a membership grade of a fuzzy set. Generally, multivariant model is to analyze samples characterized using plural variants. In this paper such smaples are also characterized by a fuzzy set.
Junzo Watada +2 more
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In this paper we will analyze data obtained from a fuzzy set, where samples are defined using a membership grade of a fuzzy set. Generally, multivariant model is to analyze samples characterized using plural variants. In this paper such smaples are also characterized by a fuzzy set.
Junzo Watada +2 more
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Multivariate analysis in surgical studies
Cirugía Española (English Edition), 2022[No abstract available]
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The discarding of variables in multivariate analysis
Biometrika, 1967In many multivariate situations we are presented with more variables than we would like, and the question arises whether they are all necessary and if not which can be discarded. In this paper we consider two such situations. (a) Regression analysis. The problem here is whether any variables can be discarded as adding little or nothing to the accuracy ...
E M, Beale, M G, Kendall, D W, Mann
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Nonlinear multivariate analysis
Evaluation News, 1990Reports (1-4 double-spaced typewritten pages) should describe tools, products, andlor services found useful by practicing evaluators. Reports should also include the context of use and sufficient informationfor interested readers to contact the user directly for more detailed information, that is, name, address, and telephone number.
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Multivariate Behavioral Research, 1981
Analysis of multivariate aptitude-treatment-interaction data is discussed. Various global hypotheses and the associated follow-up descriptions are considered and compared. Analysis procedures are illustrated using data from a science education study to describe the interaction between student reading ability and the time allowed in an individualized ...
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Analysis of multivariate aptitude-treatment-interaction data is discussed. Various global hypotheses and the associated follow-up descriptions are considered and compared. Analysis procedures are illustrated using data from a science education study to describe the interaction between student reading ability and the time allowed in an individualized ...
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Multivariate Statistical Analysis
Psychophysiology, 1973ABSTRACTGeneral multivariate statistical theory and three statistical models (multi‐variate analysis of variance, canonical correlation analysis, and factor analysis) are described. Numerical examples, mathematical notes, an annotated bibliography, and references to computer programs are presented.
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Multivariate analysis using ‘and’ and ‘or’
Mathematical Social Sciences, 1984Extensions from binary to continuous variables are considered of mathematical operators for connectives (''and'', ''or'', ''exclusive or'', etc). Using concepts from fuzzy set theory it is illustrated how such extensions can be used in statistical modelling of interactions in multivariate analysis.
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An Inequality with Application to Multivariate Analysis
Biometrika, 1975An inequality for the trace of the product of two symmetric matrices can be used to simplify the proofs of a number of results in multivariate analysis. This is illustrated on two problems: estimating the parameters of a multivariate normal population, and estimating a system of linear functional relationships between the mean vectors of k multivariate
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